Monitoring an area using multiple networked video cameras

ABSTRACT

A system and method to connect several cameras located in a given location, such as a parking garage, or area, such as in a neighborhood, is provided. The system allows each camera to function independently from each other with the purpose of recording video within the field of view of the particular camera. Image recognition processes the video to identify objects of interest and generate classification data. A search request can be generated, for example, by touching on a specific object shown on a display of the video, and networked cameras are searched for classification data that matches the search request, e.g., the selected object. Networked cameras can determine the relative spatial views of other cameras. Within a prescribed location or area, a camera or other user can access other networked cameras to extend the range of the search for the requested classification data in a “peer-to-peer” manner. Artificial intelligence software and logic is used to determine which of the surrounding networked cameras is likely to provide requested classification data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of and claims priority to PCTPatent Application No. PCT/US17/50991, entitled “Video-Based DataCollection, Image Capture and Analysis Configuration,” filed Sep. 11,2017, which claims the benefit of U.S. Provisional Application No.62/412,764, filed Oct. 25, 2016, the contents of which are herebyincorporated by reference in their entirety.

BACKGROUND OF THE INVENTION

The present invention relates generally to a system for managing therecording, collection and selective presentation of video data, and moreparticularly, to a video management system to manage a collection ofcooperating video cameras for monitoring and recording an event or areaof interest.

Good surveillance systems are helpful to provide security and protectionof people and property. For example, businesses and homeowners regularlyinstall security cameras around their businesses, homes, and otherproperty to provide video surveillance so that in the event of aburglary, theft, invasion, damage to property, or other criminalactivity the captured video data can be used to identify theperpetrators and help piece together what happened. Sometimes thecaptured video data is useful and may help the police successfullyidentify and eventually apprehend those involved in the criminalactivity.

With the availability of low-cost digital video cameras, residentialsecurity camera systems have become popular, typically with local orcloud-based video recording and storage services. However, to-date,typical home security camera systems record at relatively lowresolution, making it difficult to discern relevant details of any eventthat may have been captured. Also, although many current home securitycameras provide a source of illumination for nighttime use, suchillumination, which is usually in the form of infrared LEDs, is rarelyeffective beyond 20 feet. In addition, most criminal events take placeat night, and more importantly, most criminals are either aware of thefield of view of security cameras that may be prominently located aroundthe home and criminals make efforts to avoid being recorded by them andalso often wear clothing that obscures facial features and otheridentifying details so that even if a security camera did happen torecord a criminal in action, the recorded footage would not revealuseful information, other than perhaps a general description of thecriminal miscreant (e.g., height, build, etc.).

Another environment where security cameras are often employed is parkinglots and garages. For example, in commercial parking garages, wheredrivers pay to park their cars for a period of time, security camerasare usually employed to provide surveillance. However, typically thecameras only cover the main entrances and exits of the building andpossibly some general views of each floor. A criminal may easily bypassthe field of view of the minimal camera coverage and break into carsthat are not being surveilled or are outside or far in the field of viewof the cameras. For example, when the owner of a vehicle arrives at arestaurant that provides valet parking services, he or she relinquisheshis or her vehicle to the valet attendant, essentially a stranger, andreceives a small paper receipt in return. The attendant drives off topark the vehicle at some unknown location, typically a garage, while theowner tries to stay focused on the upcoming fine food experience.Needless to say, all vehicle owners experience a level of stress andconcern regarding any valet service because of the unknown. If theyreceive their vehicle damaged or with items missing from within, or evenwith evidence that their car was driven outside the garage, it's ahassle to file a claim and difficult to prove fault.

Similarly, when people park in open free parking lots of the typetypically provided adjacent shopping centers or businesses, even thoughthere are usually security cameras positioned throughout the area, thefootage of these cameras are not available to the owners of the carsparked in the lot.

One potential solution to these parking-related issues is the use ofvideo cameras in vehicles. So-called “dash-cams” or “car-cams” aretypically mounted to the windshield or dashboard of a vehicle and areused to record forward-facing video of the path of travel as the vehiclemoves. Various features are becoming more popular in current dash-cammodels, such as including a cabin-view camera, and motion activation,which could be used to capture video of break-in or theft events insidethe vehicle. For example, when a driver of a dash-cam enabled vehicleenters a parking lot, the dash-cam (if continually powered) may continueto record its field of view, even when the car is parked. This recordedviewing angle may prove useful if an event were to happen to the owner'svehicle inside the camera's field of view. Unfortunately, the vehicleowner would have no recorded information regarding an event occurringoutside the camera's field of view because the event would have occurredin the blind-spot of the camera. To help provide a greater field ofview, some dash-cam designs employ a 360 degree lens. Although this typeof lens does increase the field of view, the view is inherently filledwith obstructions, such as most of the vehicle, often include opticalartifacts, and may require software to resolve. Similarly, if anautomobile is subject to a forced entry incident (a break in), acar-camera in that car may quickly be stolen, knocked down, or otherwisemade inoperative. Also, in the case of an automobile accident, thecar-camera itself may become severely damaged or knocked off its mountand be unable to record or “see” the events which take place during andafter the impact. This is unfortunate since important visual evidenceoccurring after the accident may be lost.

In-vehicle camera systems also provide additional features. For example,when travelling on a road, drivers always benefit by knowing what liesahead of them. Some vehicle systems provide cameras and other sensors toscan the area immediately in front of the vehicle to provide informationto the driver and, sometimes, to assist with safety controls, such as toavoid a collision, to stay within the road, or more recently, toprovider auto-pilot and self-driving features. However, these systemsare limited to the field of view or sense immediately in front of thevehicle. Drivers may resort to other connected systems, such as on-boardguidance systems or smartphone applications, to receive additionalinformation about what lies ahead, such as traffic congestion oraccidents, road obstructions, or the like, but these apps typically relyon other drivers to actively participate, as they drive to provide theinformation to be distributed to others using the application. Theinformation often requires the participant to manually input data ormanipulate their smartphone. Of course, manually inputting suchinformation is distracting and dangerous to both the driver of one carand the neighboring vehicles and pedestrians. There are no knownapplications or devices that provide user-selectable real-time visualinformation of what lies ahead, beyond the line of sight of the driver.

Accordingly, there is a need for a system to expand the coverage of anevent or area from monitoring video cameras in the area and increase thelikelihood that useful video evidence, e.g. of a fleeing suspect, willbe obtained and overcome the shortcomings of the prior art.

BRIEF SUMMARY

According to various embodiments of the present invention, a method ofsharing video data between a plurality of remote cameras and a localcamera in wireless-communication with each other is provided. Accordingto this embodiment, a preliminary search is initiated at the localcamera to search the plurality of remote cameras by automaticallysearching the memory in each of the remote cameras for data that matchesa search criteria. In response to the preliminary search, an indicationthat the data in the memory of at least one of the remote camerasmatches the search criteria is received, which in some embodiments mayinclude identification information of the remote cameras matching thepreliminary search. Permission to perform a secondary, more detailed andcomprehensive, search of the remote cameras is requested at the localcamera. The secondary search is requested to identify video datamatching a video search query. Video data matching the video searchquery is received.

In one embodiment, the permission requesting step is performed inresponse to receiving the indication that data in the memory of one ormore of the remote cameras matches the search criteria, which optionallymay include metadata and location information of the local camera, andin some embodiments, may also include classifier data.

According to another embodiment, a method of improving the accuracy ofmatching video stored in a remote video camera with a search criteriafrom a local camera is provided. A search, based on a search algorithm,of the memory of the remote camera for data that matches the searchcriteria is requested. The search results from the requested searchbased on the search algorithm, including video data with portionsmatching the search criteria, are received and the video portions aredisplayed on a display associated with the local camera. A user confirmswhich of the video data portions actually match the search criteria, forexample, by touching a touch-screen display to select the matchingportions. The search algorithm is adjusted based on the userconfirmation to improve the accuracy of subsequent searches. Accordingto one embodiment, the adjusted search algorithm is then used to performa subsequent search of the remote device.

According to another embodiment, a method of sharing video data relatedto an event between a remote camera device and a local camera device isprovided. The camera devices are in wireless-communication with eachother. At the local camera device, a search request is created definingsearch criteria that includes metadata and a video clip corresponding tothe event. The search request is transmitted to the remote device and auser of the remote device who can authorize the requested search isnotified to seek permission for the search. The video clip is played forthe authorizing user, which may take place automatically. In response togranting permission, video data meeting the search criteria is receivedat the local camera device.

According to one embodiment, the search request includes a text messagefrom a user of the local camera device to the authorizing user of theremote camera device.

The features of described in this disclosure, and the manner ofattaining them, will become more apparent and the invention itself willbe better understood by reference to the following description of thedisclosed embodiments taken in conjunction with the accompanyingdrawings.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a schematic showing a plurality of networked client devicesand a cloud-based server according to one embodiment;

FIG. 2 is a plan view of a client device according to one embodiment;

FIG. 3 is a plan view of an exemplary vehicle using a client device,mounted to the windshield, according to one embodiment;

FIG. 4 is a plan view of an exemplary neighborhood, including variousvehicles and homes, according to one embodiment;

FIG. 5 is a plan view of an exemplary parking lot, showing variousparked vehicles, some of which including client devices, according toone embodiment; and

FIG. 6 is a plan view of an exemplary parking receipt according to oneembodiment.

The figures depict various example embodiments of the present disclosurefor purposes of illustration only. One of ordinary skill in the art willreadily recognize form the following discussion that other exampleembodiments based on alternative structures and methods may beimplemented without departing from the principles of this disclosure andwhich are encompassed within the scope of this disclosure.

DETAILED DESCRIPTION OF THE INVENTION

The Figures and the following description describe certain embodimentsby way of illustration only. One skilled in the art will readilyrecognize from the following description that other embodiments havingvarying or alternative structures may be implemented without departingfrom the principles of the disclosure. Reference will now be made indetail to several embodiments, examples of which are illustrated in theaccompanying figures. It is noted that wherever practicable similar orlike reference numbers may be used in the figures and may indicatesimilar or like functionality.

By way of introduction, the present invention relates to a videomanagement system for capturing, storing, authenticating, analyzing,accessing and presenting video files when needed. As described inApplicants' PCT Patent Application, entitled, “Video-Based DataCollection, Image Capture and Analysis Configuration”, filed Sep. 11,2017, having serial number, PCT/US17/50991, the system according to thedisclosure, manages video data from one or more of a plurality of clientdevices, each of which has at least one video camera, a processor,memory, several sensors a cellular communication module and a Bluetoothcommunication module. Each client device is either mobile—mounted to avehicle, or mounted to a fixed object so that at least one video camerarecords video data (with a field of view generally covering the forwardview of the vehicle in the case of a vehicle mounted client device). Thesensors of each client device are configured to generate metadata. Theprocessor associates the metadata with recorded video data and encryptsthe data stream. The processor, at prescribed times, transmits theencrypted video and metadata to a cloud-based server using the cellularcommunication module. The encrypted video files are stored in acloud-based server for secured access.

Referring to FIGS. 1 and 2, and according to a first embodiment of thisdisclosure, a management system 10 includes an Internet connection(cloud) 11, a network of client devices 12, and a remote server 13. Eachclient device includes a body 14, a video camera 16, a lens 18 (defininga field of view 20), controlling circuitry 22, video memory 24, RFcommunication circuitry 26, a source of power 28, and a touchscreendisplay 29. Controlling circuitry 22 includes a microprocessor 30,processor memory 32, and all other required supporting circuitry andelectronic components 34. Parent application, PCT Patent Application No.PCT/US17/50991 (incorporated by reference), describes in more detail asuitable video management system for carrying out the functionsdescribed herein. All the internal electronic components of clientdevice 12 are electrically connected to each other in such a way as toallow for their independent and supportive operation as described in theparent application.

According one embodiment of this disclosure, each client device 12 isable to communicate with server 14 and with any other client device 12within the network. This communication may include transmitting andreceiving data and instructions, depending on the particular operationbeing performed.

As shown in FIG. 3 and according to one embodiment, at least one, butpreferably most of client devices 12 are of the type that can be mountedto the dashboard or windshield 35 of a vehicle 36, taking the form ofwhat is commonly referred to as a “car-cam” or a “dash-cam.”

Referring to FIGS. 3 and 4 and according to one embodiment of thedisclosure, client devices 12 work together to form a network of videorecording devices to continuously record and store video data. Accordingto this embodiment, a fixed client device 15 may be securely mounted toa house or building structure 40, as shown in FIG. 4. In such instance,fixed client device 15 is likely not easily accessible and does notinclude touch-screen display 29. Such fixed client devices 15 willlikely be mounted high along an outside wall of the house or buildingstructure 40 and therefore not directly interactive with a user. Fixedclient devices 15 are essentially video-footage suppliers to otherclient devices 12 in the network.

According to one embodiment, if both mobile client devices 12 and fixedclient devices 15 are used in a particular network, mobile (or otherwiseaccessible) client devices 12, which do include touch-screen display 29,will provide a user interface to allow the user to set-up and lateroperate any fixed client devices 15. In one embodiment, each fixedclient device 15 could be owned by a user of a mobile client device 12,such as the owner of a home may have a security surveillance systemincluding several fixed client devices 15 mounted to various parts ofhis or her house 40 and a mobile client device 12 which is mounted tothe windshield 38 of his or her vehicle 40. Together, the fixed andmobile client devices are all part of a subgroup of the larger clientnetwork. For example, in one embodiment, all the fixed and mobile clientdevices owned by a common owner can follow the instructions of themobile client device 12 of that subgroup. This means that any searchrequests, as described below, from client devices 12 located outside thesubgroup network will be unable to directly reach any of the fixedclient devices 15—only the mobile client device 12.

Regardless, during normal operation, each client device 12 operatesindependently from the other client devices in the network andcontinuously records video data from within field of view 20 of lens 18(and also records audio data and optionally metadata, such as time anddate stamp and compass orientation, from the general area usingappropriate microphones and sensors, not shown). According to theinvention, microprocessor 30 located within each client device runs asuitable object-recognition software program, such as “TensorFlow,” or“Caffe,” to analyze each frame of recorded video, preferably concurrentto it being recorded, extract and then store all known and unknown imageclassifiers for each frame captured during recording. For example, if,during daytime, a boy runs after a yellow ball in the yard of house 40,a fixed client device 15 will record the event. Microprocessor 30located within client device 15 will apply object-recognition softwareto the images as they are being recorded and will recognize the boy asbeing a boy, the action of running, and a yellow-colored object that isshaped circular, like a ball. This information will be stored in videomemory 24, as object classifier data. If stored video data istransmitted (or otherwise transferred to another location), it mayinclude metadata and any classifier data for each frame (orpredetermined length) of video. As described below, if any stored videodata requires a computer-controlled object-based search, the computermay search the classifier data and the metadata only, since the videohas already been analyzed.

According to one embodiment, any search request from any client device12 in the network can be performed by microprocessor 30 of each clientdevice 12, whereby each client device may search the classifier data andthe metadata of the video stored in video memory 24, and also all newlyanalyzed video (in real-time). Once complete, the search results will betransmitted using RF transmitter circuit 26 to the client device of therequesting party. The transmission for any data, according to thisembodiment, may be sent directly to another client device 12, in apeer-to-peer manner, or it may be transmitted first to a cloud-basedserver 13 over a suitable wireless network service, such as LAN or 4G,either continuously, in response to a request, or at prescribed times.Server 13 may analyze and store any received data and later transmitselective stored data, including stored video data, metadata, classifierdata, or search results, to any particular client device 12, portableelectronic device, or authorized computer, after verifying permission.

As mentioned above, according to one aspect of the present disclosure,initial object-recognition and object classification work may bepreferably performed locally by each independent client device 12 duringinitial video recording (or shortly thereafter). In this regard, manyoperations, such as object searching, may be performed efficiently andeffectively using only a single client device, or select client devicesbased on factors related to the object being searched, or all of thenetworked client devices, simultaneously. By controlling which clientdevices are enlisted to assist in a search request, the searchingbecomes quicker, more accurate and more efficient than searchesperformed using conventional security systems, as described below.

According to one embodiment, cloud-based server 13 is not required toperform many of the operations and functions of the present invention,since client devices 12 are networked and may effectively communicatewith each other, in a peer-to-peer manner and perform many functionsindependently. However, in some cases, being able to have client devices12 communicate with cloud-based server 13 is beneficial and preferred.Depending on conditions, raw video data may be sent to server 13 withoutfirst performing object recognition and without providing any classifierdata. In such instance, processors (not shown) at server 13 may useobject recognition software to analyze the received raw video data andgenerate classifier data. By doing this, memory and processor timewithin each client device 12 may be freed up. As mentioned above, thisclassifier data may be used to assist in a search request at a latertime, as described in greater detail below.

According to one embodiment, by way of example, during an event locatedwithin field of view 20 of at least one networked client device 12, someinformation will be recorded by video camera 16 of at least one clientdevice 12. A user of that particular client device 12 may reviewrecorded footage of the event on touch-screen display 29 and see asection of video that appears to show “objects of interest.” This couldbe an image of a face of a suspect involved in the event or perhaps ared baseball cap the suspect appeared to be wearing in the capturedvideo. The user decides he needs more footage from other networkeddevices to help locate him in the neighborhood and warn others of hiswhereabouts. The user sends out a search request. According to oneembodiment of the invention, the user may instruct the local clientdevice 12 to send out an automatic search request based on the sectionof video footage that shows the “objects of interest.”

According to one embodiment, microprocessor 30 of local client device 12transmits the object classifier data of that section of video and othernecessary data (such as metadata) to nearby (or all, or select) clientdevices 12 of the network and instructs those devices to search theirrespective video memory 24 for any images (or video clips) whose objectclassifiers match, within a predetermined acceptable level of accuracy,the object classifiers of the search request. Nearby client devices 12are then instructed to transmit any “hits” from the search back to thelocal client device 12 for quick review. A hit may include a stillimage, or a video clip showing a predetermined amount of time before andafter the matching object classifier, such as 30 seconds before andafter.

The user may then quickly review the received hits and select any thatappear to be particularly relevant and use this information to refinethe search. The user at this time may further elect additional “objectsof interest” from any of the images or video clips of the received hitsto help narrow down a secondary revised search. Microprocessors 30 woulduse the specific object selections made by the user to “fine tune” thesecondary searching efforts, likely yielding more accurate results, thesecond time around. By providing the human user a chance to review videoclips from a search and further classify initial search hits by levelsof importance allows the computer to fine-tune searching criteria, whichwill likely improve the accuracy of future searching.

An “event” may be, for example, a crime in progress, an accident, aparty or a social gathering, or may just be a point of interest, such asthe Golden Gate Bridge.

Alternatively, in one embodiment, the user may initiate a manual searchto other client devices 12 on the network for an object of interest thatthe user captured on his client device 12. The user, as before, simplytouches on display 29 of his client device, the object or objects thathe wishes to search. For example, the user wishes to find more footage(and the location of that footage) that includes any red baseball capsso he initiates a search by selecting the baseball cap on display 29 ofhis client device 12 (by touching the baseball cap on the image on thedisplay 29) when it appears during the playback of a recorded videoclip. Microprocessor 30 of his local client device 12 is then able toidentify the selected object using object recognition software. Hisclient device 12 then uses RF communication circuitry 26 to send out asearch request to select client devices 12 nearby. Microprocessor 30knows the location and identification of all client devices in the area(either by communicating with server 13, or using RF ranging techniques,such as BLE beacons, or WiFi beacons) and can use this information toselect any of them to search their video memory for any footageincluding a red baseball cap.

According to another embodiment, microprocessor 30 analyzes the objectclassifier data of the video clip showing the selected object (in theabove example, the red baseball cap) to determine its speed anddirection of movement (assuming the selected object has moved from thefield of view). Once this is determined, microprocessor 30 compares thedirection of movement with the locations of networked client devices andtheir respective fields of view 20 to calculate which client devices aremost likely to show the selected object in their stored video footage,based on the movement of the selected object. Since the direction andspeed of the object of interest is calculated, and the relativelocations of each surrounding client device 12 is known, then anestimated time of arrival (ETA) when the object of interest will enterthe field of view 20 of the different surrounding clients devices canalso be calculated. The calculated ETA can be used during the search tonarrow the data to be searched. Now selected surrounding client devices12 (or cameras) need only search their respective memories for theobject of interest (as defined by classifier data) around the calculatedETA for each particular client device 12.

For example, referring to FIG. 4, if the suspect with the red baseballcap is shown in the video clip running North from house 50 just as thesuspect leaves the field of view of local client device 54,microprocessor 30 of the local client device 54 will transmit a searchrequest initially only to networked client devices located North of thelocal client device 54, around house 56 (to search their respectivememories just before and after the calculated ETA for the various knownclient devices located to the North), in the example shown in FIG. 4.This will speed up the searching process. If no results are found, thenthe search request will expand to additional client devices in the area.If a rate of speed is known of the object of interest, such as a personor a vehicle, but its direction is either not known, or is expected tochange, then the search request can simply be applied to all clientdevices that encircle the location of the requesting client device 12,again searching their respective memories only a prescribed time beforeand after the calculated ETA for the first perimeter of client devices12. If nothing is found, the perimeter can be extended outward. If aclient device provides a confirmed “hit”, then the searching algorithmcan use the information to update the search request, perhaps todifferent client devices, depending on any new information, such as anew speed, a new direction of travel, etc.

According to another aspect of one embodiment, any networked clientdevice 12 may send a search request to any other client device 12 in thenetwork, following the instructions of a searching algorithm used by allnetworked client devices 12. For example, a first client device 12 a mayinitiate a search by instructing a second client device 12 b to searchfor a particular object of interest. If that second client device 12 bfails to locate the selected object in its video memory during a similartime period as the original event (as determined by metadata), then thesecond client device 12 b will automatically extend the area ofsearching by sending out its own search request to additional nearbyclient devices 12 c-12 n.

Regardless of the type of search being requested, the user may includeadditional classifiers which may be included as data on any memory chip.For example, the user may type directly into his or her local clientdevice (or use voice or other form of input) to state that the object ofinterest is a small dog running East. Microprocessor 30 will be able toconvert the inputted description (e.g., text or voice) intocomputer-understood classifier data and carry out the search request tonearby client devices, in this case, located to the East.

While client devices record video, according to one embodiment, varioustags may be applied, either by the driver, through voice, text, or atouch-screen action, or automatically, by continuously using objectrecognition software on all objects appearing in field of view 20 ofcamera 16. The user may simply speak, as he or she is driving, an objectthat he or she sees (and is therefore also recorded by client device 12,such as “sunset,” “Tesla,” “Uncle Bob,” etc.). These tags will causemicroprocessor 30 to associate the tag description (i.e., a classifier),with the object that appears on the recorded video tape at that momentby creating a metadata record. Manual and automatically attached tags(subject matter labels) in video metadata allow the system to moreefficiently search as it narrows down candidates for joining and sharingdevice views and captured footage. Automatic tagging allows the objectrecognition software to identify objects automatically. The user isasked on occasion to confirm that the computer is correct for certainrecognitions, such as confirming that the computer correctly recognizedUncle Bob, or the Grand Canyon, etc. The confirmation by a human allowsthe system using artificial intelligence (AI) algorithms to learn and toincrease prediction accuracy over time during future searches andrecognition and further decrease search time and processing powerrequired for these systems and operations. Specific combinations ofclassifier data will be common triggers for automatically applied tags.For example, a detected cluster of orange pixels within a recorded scenemay indicate many different objects, but if the orange cluster of pixelsis bouncing up and down, this added information narrows the potentialobjects to a few, including the likely classification of a basketballbeing bounces on a court.

According to one embodiment, a neural net determines which clientdevices are most likely to return matches within the timeframe requiredto search based on several factors, including, for example, which clientdevices 12 have opted in and which have opted out, the GPS location ofthe client device at the time of the event, the amount of memory on thedifferent client devices being queried (how much video has been storedin the device's video memory), the speed of travel of the client deviceat the time of the event, the direction of travel of the client deviceat the time of the event, and other suitable factors. Referring again toFIG. 4, if a vehicle 60 with a client device 62 drove past the eventlocation (house 50), at the same time, but was travelling 65 MPH atnight, its video footage will be less likely to be helpful.

Once surrounding client devices complete their respective searches oftheir stored video memory 24, they will each transmit search resultsback to the local client device which initiated the search request,which will in turn notify the user by using touch-screen display 29, orhis or her portable electronic device.

As understood by those of ordinary skill in the art, all data that istransmitted between client devices 12, any portable personal electronicdevice, and server 13 may be encrypted using any suitable encryptionmethod.

The above-described automatic and manual searching between differentclient devices 12 of the network may be managed peer-to-peer between anyone or more of the microprocessors 30 of different client devices 12 ofthe network, or by cloud-based server 13. In such instance, andaccording to one embodiment, a cloud-based object recognition softwareand a suitable AI software gathers searching information and, asdescribed above, will use the information to determine which clientdevices 12 of the networked devices would be most likely to havecaptured a selected object of interest, and will then select thoseclient devices 12 to initiate their respective search.

In some circumstances, there may be advantages to using a cloud-basedserver 13 to manage the search requests, as well as applying objectrecognition software to captured video clips. For example, in oneembodiment, server 13 may have faster and more powerful processors andgreater memory and may also include a larger set of availableclassifiers, than those found on some client devices 12. This wouldallow server 13 to identify and search objects of interest more quickly,efficiently, and more accurately.

According to another embodiment, a search request, regardless of if itis requested automatically or manually by a user, may first notify theowner of the selected client device 12 to gain permission to access thememory of their client device. The owner being asked only has to selectan option on his or her touch-screen display, or portable electronicdevice to respond. The owner of the selected client device may reviewthe request more closely, including the video clip taken by therequestor's device (if there is one), and any comments provided by therequestor, such as “I'm looking for my dog and need your help—may I haveaccess to your cameras for the last 20 minutes? If so, please click‘YES’.”

According to one embodiment, since any potential evidence istime-sensitive, system 10 automatically perform a preliminary backgroundsearch of video memory 24 of any selected client devices 12 beforenotifying the owners of those devices to get their permission. Thisquick preliminary search allows the system to perform a quick cursoryreview of the metadata and classifier data files for any match relatingto the requested search data. If a match is found, or a suggestion thatthere could be a match is found, then the owner of that specific clientdevice 12 would be notified and permission requested to collect andtransmit the relevant data. As is further described in the parentapplication, in one embodiment, the preliminary search results, positiveor negative, may be used by the software program of system 10 toreassess the search situation to determine which other client devices,if any, should be interrogated to yield more accurate results. It ispreferred that no search results (or any data) from any client device 12that was preliminarily searched (i.e., without first notifying theowner) is saved in any memory to respect the owner's privacy. In basicterms, this approach can be summarized as one computer will searchanother computer for data relevant to a search request. If relevant datais found, the searching computer will ask for permission to copy therelevant data. If there is no relevant data found, then no data will becopied or otherwise saved. In any case, no data will be reviewed by ahuman, unless permission is given. By performing a preliminary search,the owner of a client device only has to be notified for permission toshare data if it is determined that there is a high likelihood that thatperson's device has captured footage relevant to a legitimate sharerequest.

According to one embodiment, system 10 allows for all users of clientdevices (during their initial setup) to manage how future permissionrequests are handled in advance so that they do not have to be bothered.For example, each user may opt to always grant any received permission,or always deny any received permission, always allow or deny, dependingon the neighbor who is asking, or other combinations of conditions. Ifdenying, in one embodiment, the system may remind the user that theywill only be asked for permission to share their video data if thesystem 10 has determined that their device contains content that isrelevant to the search request. System 10 will also remind the user theimportance of an open system among device owners and that an opensystem, where every member of the network shares footage when askedallows the overall surveillance system to work best for everyone.

If permission is granted in response to a search request, a moredetailed and thorough search may be performed. First, client device 12is instructed to transmit the relevant portions, as defined in thesearch request (such as requesting footage taken between 4:30 pm to 6:30pm on Nov. 3, 2017) of the video memory 24 of client device 12 to server13. Thereafter, server 13 would perform the more detailed review andsearch of the metadata and classifier data, based on the detailsprovided by the initial search request, such as specific “objects ofinterest.” If a match is found during the detailed search, server 13would notify the search requester and transmit the relevant searchresults to his or her client device 12 or portable electronic device fortheir review.

According to one embodiment, cloud server 13 uses artificialintelligence (AI) to learn more about matches and to help improve theaccuracy and efficiency of future searches. When a match is found on ashared video clip, system 10 may use AI to generate additionalclassifiers based on less obvious nearby objects to help provide moreinformation for any additional searching. For example, if a suspect wascaptured in the video of one client device wearing a red baseball cap,and then it is revealed that footage from a shared device shows a manwearing a red baseball cap running North and also wearing a gold watch.System 10 would identify the gold watch as a supporting objectclassifier and would now search for a man heading North wearing a redbaseball cap and/or a gold watch (just in case he removes his cap as heruns). Also, as mentioned above, if system 10 locates a match, but thematch is within a range of uncertainty, such as for example 90% certain,system 10 may ask for human assistance to validate the proposed matches.System 10 uses information uncovered from shared video data and thelocation information of the shared client devices 12 to continue toidentify additional batches of searchable client devices 12 based onwhich devices found matches (e.g., devices North of the target allreturned matches, whereas devices located West, East, and South foundnone). Also, system 10 may use object recognition, tracking software,and AI algorithms to determine not only the classifier associated withthe object of interest, but details of how that object of interest ismoving across the field of view of the particular camera. System 10 willeffectively predict the trajectory of the object of interest from thefield of view of the initial client device to other areas in theneighborhood and based on this trajectory, system 10 (or the initialclient device 12) will query nearby client devices that intersect withthe calculated path or trajectory of the object of interest. Forexample, if a suspect is captured running North, across a field of viewof a first client device 12, that client device and determine that thereis a high chance that the suspect may appear in the respective field ofviews of client devices 12 (including fixed cameras 15) located to theNorth of the first client device. Therefore, client device wouldinitially only query those client devices located to the North and wouldnot bother the client devices located to the East, West, and South.

According to one embodiment, system 10 will eventually becomesufficiently trained to identify which client devices of the network mayhave captured relevant footage by using an iterative process thatinvolves having a human verify which of any matching video footage fromvarious client devices actually match the requested search information.System 10 can then learn and fine-tune the search criteria based on thehuman only selecting those that are 100% matching, and also learn fromthe proposed matches that were not selected, essentially asking “Whywere the false-matches considered a match?” System 10 can then use thisinformation to improve the accuracy and efficiency of future searching.By having human input, the object-recognition and searching system canbe improved over time. At the same time, the system is capable oflearning to detect false positives provided by the algorithms andheuristics and may refine them to improve accuracy in future searches.

When a match is found during a search, system 10 extracts all relevantvideo clips surrounding the actual matching frames and may includestill-frames of the matching content, and all associated metadata andclassifier data. The information is then encrypted and transmitted toall parties involved, including the person who initially requested thesearch and the person who provided the shared content. All members ofthe network could also be notified that a successful share has occurred.In one embodiment, for example, a reward system may be provided tobenefit networked users who share footage and those who actively requestsearches. Such a system would incentivize frequent sharing activitywithin the network which in turn, would increase the effectiveness andrange of the surveillance capabilities of the system.

According to another aspect of one embodiment, the network of clientdevices 12 of system 10 can be positioned throughout a neighborhood, forexample. Different sub-groups of client device owners may accept inadvance to work together by effective joining the video output with eachother so that access to each others' cameras is always available,following a pre-approved sharing agreement. For example, two neighborscan “connect” their client devices 12 with each other so that cameras 16of one house can watch the other house, and vice versa. In the case thatclient devices 12 are mobile, such as car-cams, then each car-cam in thesub-group would be able to detect the proximity of other car-cams thatare part of the same sub-group when they are nearby. This could be doneusing GPS, Bluetooth, or similar communication technology. If at leastone client device 12 of a sub-group is mobile, then they canautomatically connect and share video at any location, as long as atleast two client devices are in proximity of each other (proximity maybe, for example, located within 100 to 300 feet, but can be differentdistances depending for example on communication technology, density ofhousing, and the like).

In addition, in this embodiment, more than one client device 12 may bemoving at the time. So, in one embodiment, if two client devices aredriving near each other on a highway, then the driver of each vehiclecan activate their client device to view the output of the otherdriver's client device 12. The two drivers can essentially video-chatwith each other, in real time, and record the conversation. A method forlinking nearby client devices 12 includes providing a first video camera(a first client device 12) in a first area for creating a first data.Then, providing a second video camera (a second client device 12) forcreating a second data wherein at least the second video camera ismobile and is entering the general area near the first video camera.Then, either the first or the second camera (or server 13) detects ifthe two cameras are located in proximity to each other. If so, then datafrom at least one video camera is automatically transmitted to theother. Data is transmitted only if each owner approves of thetransmission.

According to this embodiment, joining two or more client devices as asub-group with pre-approved sharing privileges, allows each member ofthe sub-group to enjoy greater coverage of their surveillance system,since all members work together, “keeping an eye out” for each other.

According to one aspect of one embodiment, each client device 12 mayknow, or otherwise query, the location and the orientation of the fieldof view of every other client device located in the network, orsub-group. Since some or all client devices in a given network orsub-group may be mobile, there is an effort to always provide as muchcoverage within the neighborhood, or monitored area as possible,especially high-value regions within the area, such as the front doorsof houses (about 80% home break-ins occur through the front door).

According to one embodiment, sub-groups of client device members may beprovided with pre-approved sharing privileges so as to increase thevisual surveillance coverage of a particular area, such as within aneighborhood around a person's home and vehicle, attempting to providecoverage as thorough as possible. According to this embodiment, system10 determines the field of view 20 of each video camera 16 within aparticular sub-group and then creates a virtual map of the area, showingwhich regions are covered by cameras and which are not. The system thenuses this information to suggest parking locations to arriving membersof the sub-group so that their field of view can be used to help“fill-in” any uncovered regions.

For example, according to this embodiment, if a neighbor's house isstill not being “watched” by any camera or client device by 8 PM and amember of the sub-group arrives in the area, his or her client device 12will understand from history of past events that the driver lives nearbyand is on schedule to park, since it is Monday at 8 PM, and thesedetails coincide with parking history details. The system will thenalert the driver to park on the right side of the main street within 100feet. In this manner, the “blind-spot” to the neighbor's house will becovered, by the newly-parked sub-group member. In one exemplaryimplementation, the system may provide a colored indication (such as,for example, a green colored bulls-eye) on touch-screen display 29 ofclient device 12 who is just arriving in the neighborhood. The bullseyewould be centered on the perfect orientation for camera 16 of thatparticular client device to ensure complete coverage in the area definedby the sub-group.

According to one embodiment, a method for instructing the driver of avehicle supporting a first video camera (client device) having a firstfield of view, where to park within an area, comprises first providing aplurality of video cameras (client devices) for continuously recordingdata within the area. Each of the plurality of video cameras are incommunication with each other as part of a network. Each video cameraincludes a lens having a field of view, a memory for storing data, aprocessor, and a system for transmitting and receiving data. A next stepincludes having the first video camera use GPS or Bluetooth technologyto determine the relative geolocation of each of the plurality of videocameras in the area. After that, the locations of any hidden regions orblind-spots (areas that are not covered by the field of view of anycameras in the area) are determined by the system. Finally, the system(which could be server 13, or any client device in the network instructs(or suggests) where the driver of the vehicle entering area should parkso that the field of view of his or her own client device 12 will helpeliminate a blind-spot in surveillance coverage of the area.

Alternatively, according to a variation of the above-describedembodiment, a driver entering a neighborhood may be provided with avisual “coverage map” on display 29 of his or her client device 12showing the areas of coverage of the immediate area around his or hervehicle, as he or she drives, looking for an available parking space.Here, the driver searches for parking spaces in the area based on thenumber of surrounding client devices covering the particular open space,as shown on the coverage map. For example, if the coverage map showsfour cameras covering one open space (i.e., the field of view of each ofthe four cameras would include the subject parking space) and only onecamera covering another parking space, the driver will select themore-covered open parking space, since he or she would want more cameraseffectively watching his or her parked vehicle.

According to another embodiment, a first client device 12 is used todetect an event recorded within its field of view 20 and alert otherclient devices 12 located within a prescribed area around the firstclient device 12. Object recognition software can be used by the firstclient device to help detect certain events, such as when a meter-maidor a street-sweeper is approaching on the street. In this example, thefirst client device 12 will view and record and recognize the object ofinterest (such as a street-sweeper) approaching and use additionalinformation, such as a history of when the street-sweeper usuallyoperates on the particular street. If it is determined that the streetsweeper is scheduled to clean the that street, the first client devicecan then transmit an urgent notification to other client devices in thearea so that the owners of the affected vehicles can move their vehiclebefore it is too late. Other client devices 12 located near each othercan work together to confirm details about an event, such as in theabove example of the street-sweeper, multiple client devices 12 can beused to determine the direction and speed of the sweeper as it movesdown the street. The notification sent to the owners of the other clientdevices 12 may include an approximate time when the street-sweeper willarrive at each respective vehicle. This time of arrival estimate may becalculated using GPS. Similar notifications can be transmitted in theevent of a break-in or crash.

According to another embodiment, one client device 12 may summon othernearby client devices 12 to an area where an event has taken place, suchas the scene of an accident or a traffic stop. By doing this, thesummoned client devices will become witnesses to the event (or shortlythereafter), by recording the scene of the event from different anglesusing camera 16 of their respective client device 12. According to oneembodiment, as an incentive for drivers to redirect to a nearby scene toaid a client device member, compensation may be offered in the form ofmoney or points, which may be applied to pay for similar services,perhaps when needed in the future. When drivers accept the request, thevideo feed of their recording client devices 12 automatically share withthe requesting client device, when the two devices become close to eachother.

According to another aspect of one embodiment of the invention, at leasttwo client devices 12 located near each other may share live videofootage. For example, if at least two client devices 12 are in twodifferent vehicles travelling relatively close to each other along aroad, perhaps in traffic, the driver of a first vehicle may use his orher first client device to show all other client devices located nearby(within RF range). The nearby vehicles will appear as “car” graphicicons overlaying a map on touch-screen display 29. The first driver mayselect one of the icons by touching it on touch-screen display 29. Theselected client device 12 would then “link” with the first client device12 and share live video feed with that device so that the front view ofthe selected client device 12 appears on display 29 of the first clientdevice. In this manner, the first driver may view other areas around hisor her vehicle, such as the view of traffic up ahead, or view his or herown vehicle from behind by selecting a car behind his or her (perhaps tomake sure that their boat trailer is OK). A system according to thisembodiment would be useful in convoys wherein a group of vehicles agreeto travel together along a highway. Rear-positioned vehicles followingin the group would not be able to see up ahead owing to vehicularobstructions. To overcome this, they could simple request a live view ofthe camera of the client device 12 of the forward most vehicle so thatthe video footage of the forward-most vehicle would play on the displayof the client device of one or more other vehicles in the convoy. Inaddition to real-time video being provided, in one embodiment, the videostored in any of the client devices used in the convoy could be laterreviewed. This will improve the chances that other client devices mayhave captured field of views that may have been obstructed by oneparticular client video.

According to another embodiment, all members of a network or sub-groupcan help each other by sharing video from their respect client devices12, wherever they may be. In this embodiment, the network may beconsidered “dynamic” because for any one client device 12, the detectedclient devices located within a prescribed distance therefrom become thenetwork, however temporary. Some client devices 12 will move out ofrange, while others will enter, keeping the network of client devicessurrounding any given client device 12 dynamic. By doing this, usefulapplications may be realized.

One application according to the above embodiment, is to provideextended automatic surveillance of a vehicle whose owner uses a clientdevice 12 and parks in a parking lot. Conventional car-cams can onlyrecord video footage of whatever happens within the camera's field ofview. However, the field of view of these conventional car-cams usuallycovers only a portion of a scene located in front of the parked vehicle.A person could hit a vehicle from the side, and in some cases the rear,without being detected or recorded, since this action would take placeoutside the field of view of the camera.

Referring now to FIG. 5, an exemplary parking lot 80 with two parallelrows of dash-cam enabled cars 82 is shown according to one embodiment.All nearby client devices 12 are programmed to “connect” with eachother, for example using an ad-hoc WiFi network. Client devices 12continuously record their respective field of views 20 and are preparedto share video data with any other client device 12 member of thenetwork. With many client devices 12 located in the parking lot,invariably the many field of views would cover many different views ofthe parking lot, including surveillance coverage of all vehicles 82.Each vehicle 82 essentially watches over other vehicles so that manyvehicles will be surveilled.

If the owner of a vehicle returns to their vehicle only to see a dent inthe fender, the owner may use his or her client device 12 (or supportingapplication on their portable electronic device) to request avideo-share from any client device 12 that is either in the area, or wasknown to be in the area at a specific time. This includes mobile clientdevices 12 located in other parked or moving vehicles nearby, and alsofixed client devices, such as fixed device 86 shown mounted to a nearbybuilding (or other structure) 84, as shown in FIG. 5. Other clientdevices 12 may have pre-approved all such sharing requests in advanceoutright, or with restrictions (as further detailed in parentapplication PCT/US17/50991). The sharing status of each nearby clientdevice (both mobile and fixed devices) may appear on display 29 thecar-owner's client device 12 so that the car-owner may select specificnearby devices which are pre-approved, for example, to speed up thesharing process.

According to this embodiment, when a vehicle 82 a having client device12 enters parking lot 80, all fixed surveillance cameras 86 locatedthroughout the parking lot automatically share data with client device12. The owner of the entering vehicle 82 a will therefore effectivelyand automatically extend the field of view of his or her own clientdevice 12 by the inclusion of the collective field of views of all fixedcameras 86. Also, any client devices 12 located in other parked vehicles82 may also share their video data, thereby further extending theeffective coverage for each client device located within parking lot 80.Owners of client devices 12 located within parking lot 82 may interactwith other client devices located nearby, including sharing videofootage, searching for data from any video footage of any client device12 or fixed camera 84, and tag objects within any of the collectivevideo data. Once a client device 12 leaves the area, it automaticallydisconnects from the client devices and fixed cameras located in parkinglot 80.

According to another embodiment, a group of networked autonomous orself-driving vehicles may each include a client device 12. System 10uses positional data (GPS location of each client device connected toserver 13), to determine the location and field of view 20 of eachcamera 16 of each device 12 within a given area, such as within aparking lot. According to the invention, system 10 may automaticallyinstruct each autonomous vehicle to position themselves (i.e., park) sothat each field of view 20 from each client device 12 may bestrategically aligned for maximum surveillance coverage of a particularobject (such as a bank), or objects, such as the many vehicles in thegroup. This allows one camera 16 to surveil the vehicle of another,while other cameras of other vehicles watch others, etc.

Referring again to FIG. 5, and according to another embodiment, parkinglot 80 having many parking spaces 81 may already be provided with fixedcameras or client devices 86, mounted to various walls and poles andother permanent structures, such as exemplary building 84. Such fixedcameras 86 are or function similar to fixed client devices 15. When theowner of a vehicle, who is also a networked client device 12 user driveshis or her vehicle 82 a into lot 80, he or she automatically becomesconnected to all the fixed cameras 86 located in the lot, as well as anyother client devices 12, located in the parking lot at the time, asdescribed above. With this arrangement, a client device owner may shopin nearby stores, for example and use a supporting application on theirportable electronic device (such as a smartphone) to get a live viewthrough any of the fixed cameras provided by the parking lot management,so the vehicle owner may check up on his or her vehicle at any time.Mobile client devices 12 located in other vehicles 82 in the parking lot80 may also be accessed, with permission from the respective owners. Thevideo data from fixed cameras 86 is stored in servers and made availableto any client device owner who later requests a “share video”, within aprescribed period of time.

According to yet another embodiment, a unique code 88, such as a QR code(or other similar code, e.g., a Bluetooth beacon, RFID, or the like) maybe provided at each parking space 81 located in parking lot 80. Codes 88could be provided next to each applicable parking space, for example,for manually scanning by a driver outside their car, or on a nearby signpositioned to be automatically scanned by camera 16 of client device 12as the vehicle pulls into the parking space 81. Alternatively, a simplenumeric code, such as those typically painted on the floor could bescanned and recognized by client device 12 as the car pulls into theparking space. Codes 88 allow any driver, regardless if they are amember of the client device network or not, to access security cameras86, which are provided by the parking lot management, but preferablyonly those security cameras 86 which oversee their vehicle 82. Suchnon-members may also be able to know if other networked client devices12 were nearby at a similar date and time and provide means to request avideo-share, for example, in one embodiment, on a reward basis forincentive to cooperate with the request.

According to another embodiment, in the event that two vehicles whoseowners use networked client devices 12 hit each other in an accident, asoftware program operating in each client device 12 will instruct theimmediately transfer of all data from their respective video memories24, at least to each other and, according to another embodiment, also toeach driver's respective insurance company. The data being sent ispreferably encrypted (with an encryption key being sent by secured meansto the owner of the client device) and includes recent video data,metadata, and classifier data (during a prescribed period, before,during and possibly shortly after the accident). The sent data may alsoinclude driver profile data, such as name, picture, driver's licenseinformation, residence address, and insurance-related information. Wheneither owner of the other vehicle involved in the accident receivesinformation from each other, the recipient cannot open the informationuntil the encryption key is provided. This arrangement allows allimportant information to be safely retained, yet remains under thecontrol of the sender, since he or she is in control of the encryptionkey.

Alternatively, according to another embodiment, some or all of theabove-described information to be sent, may instead be encrypted andtransferred to a secure memory location, either locally, or at server13, and also sent to the owner's email address, for added security. Theowner of the client device will be provided an encryption key fordecryption, when needed. This information will be compiled as anencrypted package that can easily be sent, when desired, to a thirdparty, such as an insurance company. As before, the encrypted file willrequire an encryption key before access is provided.

Many of the above-described embodiments benefit members of the networkedsystem. However, according to yet another embodiment, there are somebenefits to individuals and businesses that are not members of the videomanagement network. Some of these are benefits may be enabled through acompanion application accessible on a computer or readily-accessiblekiosks.

For example, according to one embodiment, a user identifies an area, alocation, or a point of interest, such as a house, using a map displayedon the screen of a computer or portable electronic device, and wouldlike to see this area, location, or point of interest in real time. Forexample, a web-based application called “Street View” provided byGoogle, Inc. (of Mountain View, Calif.) currently provides views takenat street level of many street-fronts and public locations, but theseviews are rarely up to date, often being months or possibly years old.According to this embodiment, a user can indicate the location ofinterest to a running application, which in turn, will transmit a searchrequest, via server 13 to all client devices 12 that are either in thearea, or may be in the area within a prescribed time period, asdetermined by server 13, client device ID information, and GPS locationinformation. Client devices 12 that are at or close to the locationindicated by the search request record video footage and then, if theyaccept the request, transmit the footage to server 13 in near-real time.Server 13, through the application may, for example, notify therequesting user that video clips are available for viewing by clickingon any of the stored video clip icons shown on the user's display. Othermeans of presenting the requested data may be provided. For example, theapplication may simply display the available video, for example, as aslide-show of still images from the available video clips, as a loopingvideo clip, or the like. If system 10 determines that no users arecurrently capturing data, a targeted request can be sent to nearbyclient devices 12 to divert their destination to capture the requestedview. According to one embodiment, the system may provide compensation(offering a “bounty” with cash, rewards, or points), as described inother embodiments.

Referring back to FIG. 5, and also FIG. 6, and according to yet anotherembodiment, paid parking lot or garage 80 is provided with fixedsecurity cameras 86 which effectively surveil every parking space 81 (orall “vital” points of view, including entrances and exits, and as manyparking spaces 81 as possible). When a driver enters garage or lot 80and receives a ticket 100, as shown in FIG. 6, ticket 100, according tothis embodiment, will indicate his or her assigned parking space 81 (forexample, G112 as shown, by way of example, in FIG. 6). QR code 88 mayalso be provided on the ticket and, if also provided, would match the QRcode at the actual parking space (in other words, each parking spaceincludes its own dedicated QR code 88). Other codes may be used asdescribed above. According to this embodiment, drivers who use clientdevices 12 and those that don't can use this system.

After the user parks his or her vehicle 82 in the assigned space 81, heor she may, at any time thereafter, scan the provided QR code 88,located on ticket 100. QR code 88 will automatically open a program(which must first be downloaded to the user's portable electronicdevice), which will allow access to live camera footage of the user'sassigned parking space 81, as viewed by one or more fixed cameras 86positioned throughout garage or lot 80.

In such instance, as described above, that QR code 88 is provided ateach parking space 81, the owner of the car will have access to at leastone security camera, if available, whose field of view includes all or aportion of the driver's vehicle.

In all related embodiments described in this application, the videofootage may be stored at a server and may be made available fordownloading by verified customers of parking garage (eithercomplementary or for a fee) or lot 80 for a period of time (such as, forexample, for 2-3 weeks). The available footage may be preferablyrestricted to footage that only showed the user's vehicle and only forthe time that the user's vehicle was parked in the assigned parkingspace 81. The owner may use this service should something happen to hisor her vehicle while parked in garage 80.

According to another embodiment, the above parking surveillance systemmay also be used with valet parking services. According to thisembodiment, a driver relinquishes his or her vehicle to a valetattendant, who then gives the driver a valet receipt and proceeds todrive the vehicle to a parking lot or garage. The receipt will include aQR code which functions as above, but now the valet attendant will firstpark the vehicle in any available parking space in and then input intotheir database the space ID that currently holds the parked vehicle. Asbefore, surveillance cameras positioned throughout the parking facilitywill capture and record all parking spaces. At any time after thevehicle is parked and the parking space ID is associated with the codeprovided to the vehicle owner, the owner of the vehicle may use the QRcode provided on his or her valet ticket to automatically open thevalet's website, or similar application and access live video feed (orother information) for his or her vehicle. If the QR code does not havean associated parking space when the user trys to access the system, forexample, if the valet attendant has not yet assigned a parking space 81to the vehicle, then the user can be given a “processing” message, aview of the entire parking area and/or an option to directly contactvalet to ask why access is not yet available.

QR code 88 will cause the application to interrogate the server'sdatabase to link QR code 88 with one or more of surveillance cameras 86,the ones that show the user's vehicle 82. The user may then view livevideo footage showing his or her vehicle in the assigned parking space81. As before, the footage is available for a length of time thereafter,such as, for example, 2-3 weeks.

In an alternative embodiment of the valet parking system, a “loaner”client device 12 can be temporarily positioned in a vehicle by a valetattendant to provide surveillance while the vehicle remains parked ingarage or lot 80. Temporary Client device 12 remains in vehicle 82 andthe owner, as in the above embodiments, continues to have with fullaccess to inside/out views as well as fixed cameras in the lot itself.

According to another embodiment, client devices 12 of a network may beused to track any characteristic of a vehicle or an object movingthrough the network and using AI to predict future path of the trackedvehicle. For example, during an “Amber Alert,” information about asuspect's vehicle is broadcasted on everyone's smartphones, and driversare alerted to watch out for any vehicle that matches the descriptionand then alert authorities of any sightings. The present invention mayuse object-recognition software to scan all objects and other detailsappearing in field of view 20 of cameras 16 of all client devices 12located within a network. For example, if the vehicle description forthe Amber Alert is a Red Late-Model pickup truck, the object-recognitionsoftware can be used to scan current recorded video from each clientdevice located in an area of interest (an area that it is believed thesuspect is likely residing at a given time), and also already recordedvideo from each video memory 24 of each client device 12 in theprescribed area. The software will notify server 13 every time a redpickup truck enters the field of view 20 of any client device 12 in thenetwork. Server 13 can then automatically report potential sightings toAmber Alert authorities, as needed. Also, notifications from the AmberAlert system may be able to automatically connect to server 13 so thatthe description information may automatically generate an appropriatesearch request to server 13, which will then determine which clientdevices 12 of the network should be notified, based on their respectivecurrent, past, and future location. Any sighting by any client device 12may establish the heading and speed of the suspect being tracked. Thisinformation may be used to notify other specific client devices 12 towatch for the suspect's vehicle, based on the predicted path of thesuspect.

According to another embodiment of the invention, client device 12 usesglobal positioning system (GPS) data and information from server 13 toautomatically help redirect drivers either towards or away from anobject of interest, depending on what the driver wants to do. Forexample, if an accident is reported ahead of a vehicle driven by aclient device user, and this is confirmed by either the client device 12of the actual vehicle that was involved in the accident, or other clientdevices 12 that detected the accident as their vehicle passed by.Regardless, system 10 will determine which vehicles, with client devices12 are approaching the accident, as traffic slows down. To help networkclients, system 10 automatically instructs select member vehicles (thatare or will be affected) to redirect their route to avoid the accidentand traffic. New directions will be sent to and displayed (and/oraudibly announced) on each affected client device 12, e.g., “Turn Leftin 500 feet to avoid upcoming accident.” Alternatively, the system mayhelp direct a vehicle to a point of interest, following a search requestor a witness request as described in several embodiments of thisdisclosure.

According to yet another embodiment, client devices 12 may be used toautomatically detect emerging inclement weather, such as snowfall, roadhazards, and potholes and notify specific client devices 12 whoserespective vehicles are approaching the area of concern. Thisinformation is automatically compiled by server 13 and shared with GPSlocation information to various relevant agencies, as needed, so thepotholes can be repaired, for example. Additionally, each client devicemay use image recognition software and collected sensor data to look forsmall changes in road conditions. Over time the data will be confirmedby many client devices 12 revealing verified and accurate data which maybe useful to other drivers or even other third parties (e.g., certaingovernment agencies or other business concerns). The system of thepresent invention can use this information in combination with othercollected information, such as detected movement of vehicles (either thevehicle that uses a client device 12, or vehicles being recorded by aclient device) wherein the detected movement suggests a road hazard,such as an accident, vehicle swerving, or sliding, or even a trafficstop. This collected event information when correlated with collectedroad condition information forms a dataset that is likely useful toinsurance companies, law enforcement agencies, road maintenanceagencies, and agencies collecting highway statistics, to state a fewexamples.

According to yet another embodiment, client devices 12 of the networkcan be used as a general communication device, as introduced above,wherein a driver may request to be connected with another driver basedon certain requirements. Client device 12 can detect if a driver isnodding off by tracking eye movement of the driver. If so, client device12 may sound an alarm and may then suggest that the driver pull over forrest. If the driver continues to drive, client device 12 will recommendthat the driver connect with another driver in the network so that thetwo drivers may keep each other awake and entertained as they drive.

According to another embodiment, a driver in need of information aboutan upcoming point of interest, or city, can request to speak withanother person in the network who is knowledgeable in the desired areaof interest, such as “I'm visiting San Francisco soon. Does anyone knowthe best places to eat?” The request can be sent to an approved list ofclient device users, or to anyone. The requesting driver is given a listof people who can help and he or she may select one of them to initiatea video-chat. The two can communicate with each other as they bothdrive. Both people will be given a live view of camera 16 of the otherperson's client device 12 (either an inside view or a forward view).

The foregoing description of the embodiments has been presented forillustration only; it is not intended to be exhaustive or to limit thepatent rights to the precise forms disclosed. Persons skilled in therelevant art can appreciate that many modifications and variations arepossible in light of the above disclosure. The language used in thespecification has been principally selected for readability andinstructional purposes, and it may not have been selected to delineateor circumscribe the inventive subject matter. It is therefore intendedthat the scope of the patent rights be limited not by this detaileddescription, but rather by any claims that issue on an application basedhereon. Accordingly, the disclosure of the embodiments is intended to beillustrative, but not limiting, of the scope of the patent rights, whichis set forth in the following.

The invention claimed is:
 1. A method of sharing video data between aplurality of remote cameras and a local camera in wireless-communicationwith each other, the method comprising: initiating, at said localcamera, a preliminary search of the plurality of remote cameras, thepreliminary search automatically searching a memory in each of theplurality of remote cameras for data that matches a search criteria;receiving, in response to said preliminary search, an indication thatthe data in the memory of at least one of the plurality of remotecameras matches the search criteria; requesting, at said local camera,permission to perform a secondary search of the memory of the at leastone of the plurality of remote cameras; requesting the secondary searchof the memory of the at least one of the plurality of remote cameras,the secondary search configured to identify video data matching a videosearch query; and receiving video data matching the video search queryfrom said at least one of said plurality of remote cameras.
 2. Themethod of claim 1, wherein said requesting permission step is performedin response to receiving the indication that the data in the memory ofat least one of the plurality of remote cameras matches the searchcriteria.
 3. The method of claim 1, wherein said secondary search checksmore data in the memory than the preliminary search.
 4. The method ofclaim 1, wherein said search criteria includes metadata and locationinformation of said local camera.
 5. The method of claim 1, wherein saidsearch criteria includes classifier data.
 6. The method of claim 1,wherein the indication comprises identification information of said atleast one of the plurality of remote cameras.
 7. The method of claim 1,wherein the receiving, in response to said preliminary search, anindication further comprises receiving an indication from a plurality ofthe remote cameras that a data in each of the remote cameras of theplurality of remote cameras matches the search criteria and furtherwherein said requesting step further comprises requesting permission toperform the secondary search of the memory of the remote cameras of theplurality of remote cameras.
 8. A method of sharing video data between aplurality of remote cameras and a local camera, each camera being inwireless-communication with each other, said method comprising:initiating, at said local camera, a preliminary search of the pluralityof remote cameras, the preliminary search automatically searching amemory in each of the plurality of remote cameras for data that matchesa search criteria; receiving, in response to said preliminary search, anindication that the data in the memory of a subset of the plurality ofremote cameras matches the search criteria; requesting, at said localcamera, permission to perform a secondary search of the memory of thesubset of the plurality of remote cameras; requesting the secondarysearch of the memory of the subset of the plurality of remote cameras,the secondary search configured to identify video data matching a videosearch query; and receiving video data matching the video search queryfrom at least one of the subset of the plurality of remote cameras. 9.The method of claim 8, wherein said requesting permission step isautomatic in response to receipt of the indication of a match from saidsubset of the plurality of remote cameras.
 10. The method of claim 8,wherein said secondary search is more detailed and comprehensive thansaid preliminary search.
 11. The method of claim 8, wherein said searchcriteria includes metadata and location information of said localcamera.
 12. The method of claim 8, wherein said search criteria includesobject classifier data.
 13. The method of claim 8, wherein saidreceiving step includes receiving identification information of saidsubset of the plurality of remote cameras.
 14. The method of claim 8,wherein said requesting step only requests permission to search saidsubset of the plurality of remote cameras.
 15. A method of sharing videodata between a plurality of remote cameras and a local camera inwireless-communication with each other, the method comprising:initiating, at said local camera, a preliminary search of the pluralityof remote cameras, the preliminary search automatically searching amemory in each of the plurality of remote cameras for data that matchesa search criteria; receiving, in response to said preliminary search, anindication that the data in the memory of at least one of the pluralityof remote cameras matches the search criteria; requesting, at said localcamera, permission to perform a secondary search of the memory of the atleast one of the plurality of remote cameras; requesting the secondarysearch of the memory of the at least one of the plurality of remotecameras, the secondary search configured to identify video data matchinga video search query based on a first algorithm; receiving video datamatching the video search query from said at least one of said pluralityof remote cameras; displaying said received video data on a displayassociated with the local camera; receiving user confirmation that thereceived video data matches the video search query; and adjusting thefirst search algorithm based on the user confirmation to improve anaccuracy of a subsequent search.
 16. The method of claim 15, furthercomprising requesting the subsequent search of the memory of the remotecamera for data that matches the search criteria, based on said adjustedfirst search algorithm.
 17. The method of claim 15, wherein the userconfirmation is based at least in part on input from a touch-screendisplay indicative of video data that matches the video search query.18. A method of sharing video data between a plurality of remote camerasand a local camera in wireless-communication with each other, the methodcomprising: initiating, at said local camera, a preliminary search ofthe plurality of remote cameras, the preliminary search automaticallysearching a memory in each of the plurality of remote cameras for datathat matches a search criteria, said search criteria including metadataand a video clip corresponding to an event; receiving, in response tosaid preliminary search, an indication that the data in the memory of atleast one of the plurality of remote cameras matches the searchcriteria; requesting, at said local camera, a permission to perform asecondary search of the memory of the at least one of the plurality ofremote cameras, the requesting a permission comprising notifying anauthorizing user of the at least one of the plurality of remote camerasby playing the video clip corresponding to the event on a display forviewing by the authorizing user; requesting the secondary search of thememory of the at least one of the plurality of remote cameras inresponse to receiving the permission from the authorizing user, thesecondary search configured to identify video data matching a videosearch query; receiving video data matching the video search query fromsaid at least one of said plurality of remote cameras.
 19. The method ofclaim 18, wherein said playing is automatic.
 20. The method of claim 18,wherein the initiating comprises sending a text message from the localcamera to the plurality of remote cameras.